Design And Implementation The System Of Urban Traffic Peccancy

As the development of transportation, the intelligent transportation system is playing a more and more important role in the modern transportation system. Recently, the traffic jams are the most bothering things in our daily life which is caused by illegal parking most of times. To solve this problem, the traffic control department has equipped cameras at the no parking area, staffs can capture vehicles which stop in the no parking area for a short of time by controlling these cameras. After this, they have to find out illegal parked vehicles by clipping videos and thus punish vehicle owners. Under the support of the innovative program of the Military of Public Security, we research and developed the illegal parked automatic capturing system, which can detect and trace vehicles in no parking area. If these are illegal parked vehicles, the system can automatic control camera and capture these cars. By running software on PC, we can get all illegal parked vehicles information.We choose TMS320DM642DSP as the system’s hardware platform. According to varies modules supplied by DSP/BIOS, we accomplished embed device’s code. Later, we debug and optimize the code by CCS integrated development environment, we focused on how to realize the TCP/IP stack of TMS320DM642and how to optimize it. In order to communicate with software on PC by network, we realized the embed device’s TCP/IP stack by the kit of NDK and optimize it according to the system’s function need.In the process of vehicle detection, images captured by the camera is analog signal, which can be changed to YUV(4:2:2) digital signal format by a decoder chip TVP5150BPS, the formatted digital signal can be directly inputted to TMS320DM642’s video port. Then, we only extract the Y component from the YUV format and compress it by4*4mean compression. We choose background subtraction method as the moving detection algorithm, the background is generated by method of average and updated adaptively by algorithm of surendra. After that, the foreground image is segmented adaptively by OTSU algorithm. So we can get a binary image which contains all moving targets information.By determine vehicles’behavior in no parking area, we choose a vehicle tracking method based on illegal parked rules. The system maintains a linked list, whose each node contains a vehicle’s state information. Each time we get a frame, we compare vehicles’information that extracted from this fame with the linked list’s each node. By doing this, we can do insert, delete operation to the linked list and update each node’s information. After all this, we only need to traverse the linked list to determine each vehicle’s behavior in no parking area.In order to manage and configure all embedded devices, we developed some software running on PC, by which, working staffs can deal with illegal events easily. The system can fully meet the requirement of Military of Public Security.